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Linear combination of forecasts with numerical adjustment via MINIMAX non-linear programming

Correa, Jairo Marlon; Neto, Anselmo Chaves; Teixeira Junior, Luiz Albino; Carreno, Edgar Manuel and Faria, Álvaro Eduardo (2016). Linear combination of forecasts with numerical adjustment via MINIMAX non-linear programming. Revista GEPROS - Gestão da Produção, Operações e Sistemas, 11(1) pp. 79–95.

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Document Language: Portuguese [português]
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DOI (Digital Object Identifier) Link: https://doi.org/10.15675/gepros.v11i1.1322
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Abstract

This paper proposes a linear combination of forecasts obtained from three forecasting methods (namely, ARIMA, Exponential Smoothing and Artificial Neural Networks) whose adaptive weights are determined via a multi-objective non-linear programming problem, which seeks to minimize, simultaneously, the statistics: MAE, MAPE and MSE. The results achieved by the proposed combination are compared with the traditional approach of linear combinations of forecasts, where the optimum adaptive weights are determined only by minimizing the MSE; with the combination method by arithmetic mean; and with individual methods.

Item Type: Journal Item
ISSN: 1984-2430
Keywords: Time Series; Combination of Forecasts; Multi-objective Programming
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 46122
Depositing User: Álvaro Faria
Date Deposited: 20 Apr 2016 10:20
Last Modified: 03 May 2019 14:44
URI: http://oro.open.ac.uk/id/eprint/46122
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